Modulation of N-nitrosodiethylamine (NDEA) induced oxidative stress by vitamin E in rat erythrocytes
Bibliographic record
Abstract
Nitrosamines, such as N-nitrosodiethylamine (NDEA), induced oxidative stress due to the generation of reactive oxygen species, which are capable of initiating peroxidative damage to the cell. The present study was designed to establish whether pre-treatment with vitamin E (40 mg/kg body wt, intraperitoneally (ip), twice a week for 4 weeks) to NDEA induced rats provides protection against oxidative stress caused by NDEA. A single necrogenic dose of NDEA (200 mg/kg body wt) was administered intraperitoneally (ip) to the rats with or without vitamin E pre-treatment and the animals were sacrificed on Day 7, 14 or 21 after NDEA administration. Lipid peroxidation (LPO) and the activities of antioxidant enzymes were determined in erythrocytes as indices of oxidative damage. The result showed elevated levels of LPO in erythrocytes with NDEA treatment, however, vitamin E pre-treated rats administered NDEA showed decreased LPO (Day 14 and 21). Superoxide dismutase (SOD) enzyme activity and the glutathione (GSH) content increased with NDEA treatment and remained high in vitamin E pre-treated group. Catalase (CAT), glutathione reductase (GSH-R) and glutathione-S-transferase (GST) enzyme activities declined with NDEA treatment; however, vitamin E pre-treated rats administered NDEA, showed elevation in the enzyme activities. Glutathione peroxidase (GSH-Px) activity increased in erythrocytes in vitamin E pre-treated rats administered NDEA, while Se-GSH-Px activity was not affected significantly. This study demonstrates that the pre-treatment with vitamin E prior to the administration of NDEA was effective in counteracting and modulating oxidative stress in rat erythrocytes in a time-dependent manner.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".